176 to 200 of 995 Machine Learning Jobs in London

encompasses the products and systems closest to the customer journey - search, pricing, payments, fare intelligence, and conversational interfaces. You will define and lead the ML strategy, team, and delivery across this domain. That means building and scaling ML and AI capabilities that measurably improve the customer experience and drive business … outcomes. The work spans traditional ML systems and emerging agentic/LLM-based capabilities. You will lead multiple ML teams through their respective team leads, reporting to the Director of AI & ML. You’ll be accountable for the people (2 ML Managers and ~10 ICs), delivery, and budget across your ...

ML Engineer (Stealth AI Company) About the company We are building a foundational intelligence platform that transforms fragmented, proprietary information into durable institutional intelligence - enabling organisations to reason faster, preserve context, and compound knowledge over time. We are starting with information-dense, judgment-heavy industries where decision-making under uncertainty … organisational knowledge evolves We are intentionally not: a workflow automation tool a chat UI on top of documents a standalone 'knowledge graph product' Graphs, ML, probabilistic reasoning, and human-in-the-loop systems are combined to solve a larger problem: How can organisations reason reliably over their own information ...

unlock them with AI. We’re hiring a Head of AI Engineering, Commercial to lead a high-autonomy tiger team of Data Scientists and ML Engineers in London. You will architect and ship production AI systems—from intelligent agents to predictive analytics—that directly reshape how our global commercial organization … advisory role. You will own the roadmap, build the team, and deliver. What you will be doing Own the AI/ML roadmap for FIS’s global commercial organization—translating strategic priorities into a sequenced delivery plan with measurable outcomes. Design, build, and deploy AI Agents at enterprise scale: automated ...

Recursion’s drug discovery platform. From model training pipelines to production deployment systems, to agent infrastructure and Large Language Models, you will ensure our ML models can operate at massive scale across our supercomputing infrastructure, both on‐prem and in the cloud. You will work cross‐functionally across ML engineering … data science, and research teams to translate requirements into robust, scalable ML infrastructure solutions. In This Role You Will: Enable AI/ML, LLM, and Agentic Systems teams for scale – build and operate platforms that allow data scientists and ML engineers to train, deploy, and monitor models across Recursion ...

actively to codebases and architectural decisions Developing and deploying production-grade AI systems using Azure, Databricks and Generative AI tooling Owning the implementation of ML pipelines, APIs and data integration workflows Enforcing MLOps best practices, coding standards, version control and performance optimisation Collaborating cross-functionally with data scientists, product managers … Python proficiency (async programming, concurrency, multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation ...

Lead high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement.* Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes.* Lead the modeling framework for complex systems, guaranteeing … related quantitative field, or equivalent experience in practice.* Experience: 5+ years of professional data science experience. You have delivered at least 3 data or ML products from problem definition to production deployment and monitoring.* Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics.* Hands-on experience ...

Lead high-impact data science initiatives end-to-end, including problem framing, methodology selection, experiment development, implementation partnership, and impact measurement. Build and deliver machine learning and reinforcement learning solutions to improve player engagement, retention, monetization, and operational outcomes. Lead the modeling framework for complex systems, guaranteeing … related quantitative field, or equivalent experience in practice. Experience: 5+ years of professional data science experience. You have delivered at least 3 data or ML products from problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands-on experience ...

ML Ops Engineer Role Overview Were hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: youll design and operate data pipelines that feed models ...

mentorship while helping shape the technical foundations of the business. Strong junior and mid-level engineers are encouraged to apply. 🔹 Build and deploy ML models 🔹 Work with time-series, sensor & geospatial data 🔹 Develop real-world AI systems 🔹 Influence product and technical direction from day one Looking for experience with: ✔ Python … PyTorch/TensorFlow/Scikit-learn ✔ Production ML systems ✔ AWS/GCP/Azure Bonus points for MLOps, signal processing, maritime or offshore energy experience. If interested, please apply or message directly. ...

hiring in Miami, London and Milan. Description -- Role: expected to contribute to production grade proprietary trading systems, deploy state of the art AI/ML, develop novel AI/ML models, experiment with and develop novel trading ideas, explore new datasets. -- Required: experience training ML models end to end (from … data processing to fine tuning), experience training across transformers/generative models/RL, publications in either top tier ML conferences (e.g., NeurIPS, ICLR, ICML, JMLR, etc.) or top scientific journals, top tier institutions/industry experiences. -- Positives but not requirement: PhD. Reference: AMC/AHU/NW/SPH001 ...

looking for an engineer with experience in low-level systems programming and optimisation to join our growing ML team. Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing … passion for solving interesting problems, we have a feeling you'll fit right in. What we’re looking for: An understanding of modern ML techniques and toolsets. The experience and systems knowledge required to debug a training run's performance end to end. Low-level GPU knowledge of PTX, SASS ...

market. The product team is ambitious and well-resourced, with a long-term roadmap and real appetite for innovation - including AI and machine learning integration. The Role You'll be the voice of the user across the product team - owning the research programmes that shape product direction … research - interviews, surveys, observational studies, and usability evaluations Translating findings into personas, journey maps, wireframes, prototypes, and user flows Designing UX for AI and machine learning-powered features, including efficacy testing and governance Running usability tests, iterating on designs based on evidence Collaborating with product managers, engineers ...

purpose-built for marketing, trained on real marketing workflows and deeply integrated with ad platforms, CRMs, brand assets, and analytics tools. As an ML Engineer, you’ll design, build, and ship production ML systems that power our core product and agent ecosystem - from real-time chat and workflow automation … autonomous agents like daily performance briefings and competitor tracking. What you’ll work on Develop and deploy ML/LLM systems for marketing-specific workflows (reporting, analysis, review, compliance) Build agentic systems with persistent memory, tool use, and workflow orchestration Integrate models with live data sources (Google Ads, GA4, Meta ...

creator ecosystem, and developing models for strategic content valuation. Multi-objective balancing and long term measurement. We rely extensively on state-of-the-art ML around personalization, deep learning, causal inference, optimization, ranking and recommendation. What You’ll Do Within the Sharechat AI team, we are looking … engagement while minimizing server and cloud costs of serving large scale models, and act as a subject matter expert in the recommender systems and ML ranking domains. You would be joining us at an exciting time! The science behind recommendation systems is rapidly changing, and we’re making big progress ...

Hiscox Underwriting Group Services Ltd (HUGS) is seeking a Principal Machine Learning Engineer to lead the technical strategy for production ML systems in the London/York area. This position requires extensive experience in machine learning engineering and an ability to influence the adoption … within the organization. The ideal candidate should have a strong background in Python, MLOps, and deep learning practices, with a focus on operational excellence and software quality. Opportunities for mentoring and collaborative work in a fast-paced environment await you. #J-18808-Ljbffr ...

Engineer with strong software engineering fundamentals to join our team of domain experts and researchers. You will be responsible for building robust, scalable ML systems that bring our foundation models for retail from prototype to production. Key Responsibilities Design and build production‐grade ML infrastructure, including training pipelines, model … serving, and monitoring systems. Collaborate with research engineers to translate experimental models into reliable, maintainable software. Optimise ML systems for performance, scalability, and cost‐efficiency in cloud environments (distributed clusters, GPUs). Establish engineering best practices for ML development, including testing, CI/CD, and code review standards. Progression Timeline ...

SeniorML Systems Engineers - Vision ML/Visual Data Processing A privately backed AI technology company operating at the intersection of machine learning in the media industry. You will own core ML infrastructure end to end, from data ingestion and curation through to distributed training and production inference, working … scale multimodal datasets (video, embeddings, metadata). This is not a research role. The focus is on productionising models, building reliable platforms, and making ML systems fast and scalable in a real production environment. The ideal profile is an ML engineer transitioning from research into platform ownership - someone ...

system evolution. Develop and maintain backend Python services, APIs and microservices supporting AI-powered applications. Integrate Large Language Models (LLMs), AI services and machine learning capabilities into production systems. Own complex technical challenges relating to performance, reliability, scalability and system integration. Implement and support DevOps and MLOps practices … from design through deployment and support. Strong stakeholder management and communication skills. Desirable Experience Experience with machine learning solutions and ML model deployment. Experience with computer vision technologies. Exposure to MLOps frameworks and AI infrastructure management. Experience building AI assistants, chatbots or agent-based systems. Knowledge of cloud ...

Machine Learning Engineer £700-750/day overall assignment rate to umbrella Fully remote 6 month initial Apply today to join a forward-thinking, tech-driven FTSE 100 organisation using data science and AI to enhance customer experience, optimise supply chains and drive sustainable growth click apply ...

needs. You will also influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation. Responsibilities Set AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI, aligning work to product goals, customer needs, and business priorities. Lead and develop high-performing teams by coaching … cross-functional leaders, shaping roadmaps, translating technical insights, and aligning teams on customer and business impact. Requirements Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or a related quantitative field, or equivalent practical experience. Strong technical expertise across modern data science methods, including machine learning ...

team undergoing significant transformation, moving from reactive operational delivery into a highly product-led, data-driven environment with a strong focus on automation, machine learning and scalable product strategy. This is a genuinely high ownership role where product thinking, leadership and execution matter more than ticking every domain … representment success and operational efficiency • Collaborating with senior stakeholders across multiple business functions to influence direction and prioritisation • Partnering with engineering teams to build machine learning-driven capabilities focused on predictive dispute defence • Translating complex payment ecosystem challenges into clear product opportunities and deliverables • Scaling and growing ...

date with its features, capabilities, and roadmap Tungsten Solutions Knowledge : Maintain a firm understanding of all primary Tungsten Automation solutions and offerings AI and ML Capabilities : Leverage AI and machine learning capabilities, including natural language processing (NLP), computer vision, and LLMs, to optimize document processing, data extraction … term success of Tungsten Automation solutions Production AI Experience : Leverage experience with deploying, monitoring, and maintaining AI/LLM models in production (e.g., Azure ML, AWS Sagemaker, or Kubernetes-based ML pipelines) Thought Leadership : Provide thought leadership on AI-driven automation trends and best practices, both internally and externally Collaboration ...

complex technical outputs into clear, compelling insights for senior stakeholders. Drive experimentation and optimisation initiatives to improve performance across commercial channels. Champion AI and machine learning innovation, staying ahead of industry best practice. Promote ethical data use, governance and compliance across all analytics initiatives. What You Bring … working with large datasets and distributed computing tools such as Azure Synapse and Snowflake. Familiarity with data transformation tools (Databricks, Azure Data Factory) and ML platforms (Azure ML, TensorFlow). Experience with data visualisation tools such as Power BI. Strong commercial acumen with the ability to translate business problems into ...

Recraft is looking for a Junior Machine Learning Engineer in Greater London to work on real-world AI applications, gaining crucial experience in model development and deployment. You will collaborate with research scientists and engineers to enhance Recraft’s AI-driven creative tools. This role involves training … evaluating machine learning models and contributing to experiments to improve system efficiency. Ideal candidates are pursuing relevant studies and have strong Python skills. #J-18808-Ljbffr ...

Description White Collar Factory (95009), United Kingdom, London, London Engineering Manager – Software & ML About this role We are looking for a Software Engineering Manager who brings a solid foundation in modern development and some experience with Machine Learning environments. You’ll lead and grow a team that builds … integrate software features that are vital to the lives of credit card consumers. Nurture Talent: Coach and nurture your engineers, including those working on ML integration to achieve their technical, business, and personal goals. Bridge the Gap: Collaborate with Product Managers and Data Scientists to ensure ML models are effectively ...